1. Field of the Invention
The present invention relates generally to wireless communication. More particularly, the present invention relates to techniques for joint detection of multiple-input multiple-output (MIMO) and multi-user code division multiple access (CDMA) signals.
2. Related Art
Wireless communications have become ubiquitous. Improving the performance and capacity of wireless communications systems is highly desirable.
Many wireless communications systems make use of code division multiple access (CDMA) to enable multiple users to share a common frequency bandwidth. CDMA can provide high capacity in some wireless systems, including for example, cellular networks. In CDMA, users' transmissions are encoded with spreading codes. Ideally, spreading codes for different users allow the transmissions for different users to be separated without interference. In practice, some interference (“multi-user interference”) occurs, which can be eliminated by various multi-user detection algorithms, including for example, interference cancellation. Performance of interference cancellers has sometimes provided limited performance, in part due to errors in estimating the interference caused between users.
Improved interference cancellation techniques have been developed that use iterative processing. The typical iterative approach uses the output of the interference canceller to estimate user data symbols, which are fed back into the interference canceller to provide improved cancellation of interference and successively refined estimates of the user symbols. This typical approach, however, suffers from various problems, including no guarantee of convergence, and suboptimal performance. Other known approaches frequently realize only a fraction of the potential channel capacity.
An alternate approach to dealing with multi-user interference is to perform joint demodulation of the multiple users. For example, maximum likelihood sequence estimation (MLSE) may be performed which accounts for both multi-user interference and symbol-to-symbol memory introduced by forward error correction (FEC) encoding. Although MLSE can provide excellent performance, MLSE is prohibitively complex when there are a large number of users since the complexity of MLSE grows exponentially with the number of users. One method that avoids this exponential complexity, yet results in the same performance as MLSE, is minimum mean square error (MMSE) detector with soft cancellation as described by X. Wang and H. V. Poor, “Iterative (Turbo) Soft Interference Cancellation and Decoding for Coded CDMA”, IEEE Trans. Commun., vol. 47, no. 7, pp. 1046-1061, July 1999, and herein incorporated by reference. A K user system may, in general, require inversion of a K-by-K matrix for each user symbol and for each iteration. Hence, the processing complexity of suboptimum receivers can be of the order of K3. Although some simplification of the processing can be obtained using iterative steps, such approaches still require processing complexity of the order of K2 or greater per each user symbol for each iteration. Hence industry has continued to search for improved multi-user detection techniques.
New wireless communications techniques, such as multiple-input multiple-output (MIMO), are also being introduced which have the potential to provide high capacity. In MIMO, multiple antennas at a transmitter are used, where different symbols may be transmitted on each antenna, providing increased capacity. Multiple antennas at the receiver are typically used, to allow the separation of the symbols from each transmit antenna. Theoretically, MIMO channels can provide capacity which increases linearly with the number of antennas. Interference between the different symbols from different antennas, however, sets limits on practical application of MIMO. Hence, handling interference becomes an important aspect of achieving the potential capacity of a MIMO system.